Workflow
Single-cell transcriptomics of cells infected with influenza virions carrying barcodes. This experiment allows accurate detection of the number of unique virions infecting each cell and its resulting impact on the transcriptome. The single-cell transcriptomics were performed using 10X Chromium.
The basic steps in the analysis are as follows:
- The FASTQ files from Illumina sequencing the 10X transcriptomic libraries are generated using cellranger mkfastq. See the summary results in 10X FASTQ files.
- Transcriptome quantification is performed by aligning the 10X FASTQ files with STARsolo. STARsolo also identifies the cells and creates the cell-gene matrix. See the summary results in Aligning 10X FASTQs.
- The viral tags and barcodes are analyzed in the aligned 10X FASTQ files. See the summary results in Viral tags and barcodes in 10X data.
- The cell-gene matrix is analyzed using scanpy and AnnData. See the summary results in Analysis.
Detailed software versions can be found under Rules.
Results
| File | Size | Description | Job properties | ||||
|---|---|---|---|---|---|---|---|
| <<<<<<< HEAD fastq10x_qc_analysis.html ======= fastq10x_qc_analysis.html >>>>>>> 10a41aac89852583006e92b77f0d4e2f50efd4dd | 358.6 kB | Analysis of quality-control statistics from the generation of the 10X FASTQ files using cellranger mkfastq, in the form of an HTML rendering of a Jupyter notebook. |
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| File | Size | Description | Job properties | ||||
|---|---|---|---|---|---|---|---|
| <<<<<<< HEAD align_fastq10x_summary.html ======= align_fastq10x_summary.html >>>>>>> 10a41aac89852583006e92b77f0d4e2f50efd4dd | 446.6 kB | Statistics from the STARsolo alignments of the 10X Illumina FASTQ files in the form of an HTML rendering of a Jupyter notebook. |
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| <<<<<<< HEAD fastq10x_transcript_coverage.html ======= fastq10x_transcript_coverage.html >>>>>>> 10a41aac89852583006e92b77f0d4e2f50efd4dd | 608.7 kB | Coverage plots for some selected transcript in the aligned 10X Illumina reads, in the form of an HTML rendering of a Jupyter notebook. |
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| File | Size | Description | Job properties | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| <<<<<<< HEAD hashing_trial1_analyze_cell_gene_matrix.html ======= hashing_trial1_analyze_cell_gene_matrix.html >>>>>>> 10a41aac89852583006e92b77f0d4e2f50efd4dd | 977.9 kB | Analysis of the cell-gene matrix for hashing_trial1 in the form of a HTML rendering of a Jupyter notebook. |
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| <<<<<<< HEAD hashing_trial2_analyze_cell_gene_matrix.html | 1.0 MB | ======= hashing_trial2_analyze_cell_gene_matrix.html641.8 kB | >>>>>>> 10a41aac89852583006e92b77f0d4e2f50efd4ddAnalysis of the cell-gene matrix for hashing_trial2 in the form of a HTML rendering of a Jupyter notebook. |
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| <<<<<<< HEAD hashing_wt_rapidpilot_analyze_cell_gene_matrix.html ======= hashing_wt_rapidpilot_analyze_cell_gene_matrix.html >>>>>>> 10a41aac89852583006e92b77f0d4e2f50efd4dd | 993.4 kB | Analysis of the cell-gene matrix for hashing_wt_rapidpilot in the form of a HTML rendering of a Jupyter notebook. |
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Statistics
Configuration
Rules
| Rule | Jobs | Output | Singularity | Conda environment | Code | ||
|---|---|---|---|---|---|---|---|
| fastq10x_qc_analysis | 1 | <<<<<<< HEAD | <<<<<<< HEAD | ||||
| align_fastq10x_summary | 1 | <<<<<<< HEAD | <<<<<<< HEAD | ||||
| fastq10x_transcript_coverage | 1 | <<<<<<< HEAD | <<<<<<< HEAD | ||||
| viral_fastq10x_coverage | 1 | <<<<<<< HEAD | <<<<<<< HEAD | ||||
| analyze_gaps | 1 | <<<<<<< HEAD | <<<<<<< HEAD | ||||
| count_viraltags_fastq10x | 3 |
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>>>>>>> 10a41aac89852583006e92b77f0d4e2f50efd4dd
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| count_viralbc_fastq10x | 3 |
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| analyze_cell_gene_matrix | 3 |
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| make_fastq10x | 5 |
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| align_fastq10x | 3 |
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| index_bam | 3 | <<<<<<< HEAD | <<<<<<< HEAD | ||||
| make_refgenome | 1 | <<<<<<< HEAD |
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| get_cb_whitelist_10x | 1 | <<<<<<< HEAD | <<<<<<< HEAD | ||||
| get_cell_genome | 1 | <<<<<<< HEAD | <<<<<<< HEAD | ||||
| get_cell_gtf | 1 | <<<<<<< HEAD | <<<<<<< HEAD |